Consistent Total Traction Torque-Oriented Coordinated Control of Multimotors with Input Saturation for Heavy-Haul Locomotives
Bibliographic record
Abstract
In the coordinated control of multiple motors for heavy-haul locomotives, the input value for a motor often exceeds its maximum allowable input value, resulting in the saturation problem. A traction total-amount coordinated tracking control (TACTC) strategy is proposed to address the input saturation of heavy-haul locomotives driven by multiple motors. This strategy reduces control input and suppresses input saturation. First, a multimotor traction model with uncertain parameter perturbations and external disturbances was established. Next, a sliding-mode disturbance observer (SMDO) was designed to reduce the sliding-mode switching gain, thereby decreasing the control input. An auxiliary anti-windup (AW) system was used to weaken the effect of input saturation on tracking performance. Then, the observed value and auxiliary state were fed back to the sliding-mode controller to design a TACTC protocol and ensure that the total amount of traction torque follows the desired traction characteristic curve. Finally, the Matlab/Simulink simulation and RT-Lab semiphysical experiment results show that the proposed strategy can effectively suppress the input saturation problem of multimotor coordinated control.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".